Justin Harris, Principal Software Engineer at Microsoft with expertise in machine learning, discusses Microsoft Copilot, ML team organization, and natural language processing advancements. Topics cover the evolution of machine learning models, challenges in testing AI models, ethical considerations in AI systems, and enhancing productivity through Notion and machine learning experimentation. The podcast also explores security measures for AI assistants, token-based processing in language models, generating visual elements, optimizing voice technology, and more.
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Quick takeaways
Microsoft Copilot is a chatbot based on a large language model developed by Microsoft in 2023.
Justin Harris, a Principal Software Engineer at Microsoft, discusses natural language processing and ML team organization in relation to Microsoft Copilot.
The evolution from classical methods to large language models raises considerations on choosing the appropriate model for cost-effective solutions.
Microsoft Co-Pilot aims to enhance user experiences by exploring multi-model integration and real-time local processing for efficient AI applications.
Deep dives
Microsoft Co-Pilot Development and Launch
Microsoft Co-Pilot is a chat bot developed by Microsoft based on a large language model. Justin Harris, a principal software engineer at Microsoft, discusses the launch of Microsoft Co-Pilot in 2023 and his extensive experience in classical machine learning and neural networks. He highlights the progression from natural language processing with classical machine learning to deep learning and large language models.
Evolution of AI Models
The evolution of AI models from classical methods like support vector machines and conditional random fields to the current era of large language models is discussed. Initially, applications focused on specific models for different tasks like classification and entity extraction. With large language models, one model can address various tasks more efficiently.
Customization with Models
The discussion revolves around the potential overapplication of large language models (LLMs) to tasks that may be adequately handled by simpler models like naive base classifiers. The balance lies in choosing the right model for specific use cases, potentially leading to cost-effective and tailored solutions.
Microsoft Co-Pilot Platform Landscape
The landscape of co-pilots at Microsoft is explored, including the co-pilot platform development and its integration across various Microsoft services. The platform standardizes integrations through plugins and supports custom code integration for specific use cases.
Local Models and Future Directions
Exploration of deploying local models on user devices as a future direction for enhancing privacy and efficiency in AI applications. The potential benefits of running models locally without GPU requirements are highlighted, showcasing advancements in AI technology.
Sample Conversations and Challenges
Insights into user interactions with Microsoft Co-Pilot, including refining prompts for accurate responses and adjusting queries based on contextual understanding. Challenges in real-time transcription and translation for voice input are acknowledged, emphasizing the importance of continuous improvements in AI systems.
Team Collaboration and Multi-Model Approach
The importance of team collaboration in refining AI models and leveraging mixed models for specific tasks is discussed. Collaborations with research teams for fine-tuning models and adapting to evolving AI paradigms highlight the dynamic nature of AI development.
Future of Co-Pilot and Object Basin Library
The future direction of Microsoft Co-Pilot includes exploring multi-model integration and real-time local processing for enhanced user experiences. The Object Basin library is introduced as a tool for streaming dynamic JSON updates to clients, allowing for adaptive card modifications and efficient rendering of elements.
Microsoft Copilot is a chatbot developed by Microsoft that launched in 2023 and is based on a large language model.
Justin Harris is a Principal Software Engineer at Microsoft and has an extensive background in classical machine learning and neural networks, including large language models. He joins the show to talk about Microsoft Copilot, natural language processing, ML team organization, and more.
Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from information visualization to quantum computing. Currently, Sean is Head of Marketing and Developer Relations at Skyflow and host of the podcast Partially Redacted, a podcast about privacy and security engineering. You can connect with Sean on Twitter @seanfalconer .